Investigation of mechanisms governing emission of odorants

The literature identifies several models that describe inter-phase mass transfer, key to the emission process. While the emission process is complex and these models may be more or less successful at predicting mass transfer rates, they identify three key variables for a system involving a liquid and an air phase in contact with it: • A concentration (or partial pressure) gradient driving force; • The fluid dynamic characteristics within the liquid and air phases, and • The chemical properties of the individual components within the system. In three applied research projects conducted prior to this study, samples collected with two well-known sampling devices resulted in very different odour emission rates. It was not possible to adequately explain the differences observed. It appeared likely, however, that the sample collection device might have artefact effects on the emission of odorants, i.e. the sampling device appeared to have altered the mass transfer process. This raised the obvious question: Where two different emission rates are reported for a single source (differing only in the selection of sampling device), and a credible explanation for the difference in emission rate cannot be provided, which emission rate is correct? This research project aimed to identify the factors that determine odour emission rates, the impact that the characteristics of a sampling device may exert on the key mass transfer variables, and ultimately, the impact of the sampling device on the emission rate itself. To meet these objectives, a series of targeted reviews, and laboratory and field investigations, were conducted. Two widely-used, representative devices were chosen to investigate the influence of various parameters on the emission process. These investigations provided insight into the odour emission process generally, and the influence of the sampling device specifically.

A psychometric comparison of the Toronto Alexithymia Scale (TAS-20) and the Observer Alexithymia Scale (OAS) in an alcohol-dependent sample

Alexithymia is characterised by deficits in emotional insight and self reflection, that impact on the efficacy of psychological treatments. Given the high prevalence of alexithymia in Alcohol Use Disorders, valid assessment tools are critical. The majority of research on the relationship between alexithymia and alcohol-dependence has employed the self-administered Toronto Alexithymia Scale (TAS-20). The Observer Alexithymia Scale (OAS) has also been recommended. The aim of the present study was to assess the validity and reliability of the OAS and the TAS-20 in an alcohol-dependent sample. Two hundred and ten alcohol-dependent participants in an outpatient Cognitive Behavioral Treatment program were administered the TAS-20 at assessment and upon treatment completion at 12 weeks. Clinical psychologists provided observer assessment data for a subsample of 159 patients. The findings confirmed acceptable internal consistency, test-retest reliability and scale homogeneity for both the OAS and TAS-20, except for the low internal consistency of the TAS-20 EOT scale. The TAS-20 was more strongly associated with alcohol problems than the OAS.

Data-driven background dataset selection for SVM-based speaker verification

The recently proposed data-driven background dataset refinement technique provides a means of selecting an informative background for support vector machine (SVM)-based speaker verification systems. This paper investigates the characteristics of the impostor examples in such highly-informative background datasets. Data-driven dataset refinement individually evaluates the suitability of candidate impostor examples for the SVM background prior to selecting the highest-ranking examples as a refined background dataset. Further, the characteristics of the refined dataset were analysed to investigate the desired traits of an informative SVM background. The most informative examples of the refined dataset were found to consist of large amounts of active speech and distinctive language characteristics. The data-driven refinement technique was shown to filter the set of candidate impostor examples to produce a more disperse representation of the impostor population in the SVM kernel space, thereby reducing the number of redundant and less-informative examples in the background dataset. Furthermore, data-driven refinement was shown to provide performance gains when applied to the difficult task of refining a small candidate dataset that was mis-matched to the evaluation conditions.

Exploiting multiple feature sets in data-driven impostor dataset selection for speaker verification

This study assesses the recently proposed data-driven background dataset refinement technique for speaker verification using alternate SVM feature sets to the GMM supervector features for which it was originally designed. The performance improvements brought about in each trialled SVM configuration demonstrate the versatility of background dataset refinement. This work also extends on the originally proposed technique to exploit support vector coefficients as an impostor suitability metric in the data-driven selection process. Using support vector coefficients improved the performance of the refined datasets in the evaluation of unseen data. Further, attempts are made to exploit the differences in impostor example suitability measures from varying features spaces to provide added robustness.

The home stigma : adverse selection in ADRs and the home capital market environment

We investigate whether characteristics of the home country capital environment, such as information disclosure and investor rights protection continue to affect ADRs cross-listed in the U.S. Using microstructure measures as proxies for adverse selection, we find that characteristics of the home markets continue to be relevant, especially for emerging market firms. Less transparent disclosure, poorer protection of investor rights and weaker legal institutions are associated with higher levels of information asymmetry. Developed market firms appear to be affected by whether or not home business laws are common law or civil law legal origin. Our finding contributes to the bonding literature. It suggests that cross-listing in the U.S. should not be viewed as a substitute for improvement in the quality of local institutions, and attention must be paid to improve investor protection in order to achieve the full benefits of improved disclosure. Improvement in the domestic capital market environment can attract more investors even for U.S. cross-listed firms.

Selection and optimization of piezoelectric polyvinylidene fluoride polymers for adaptive optics in space environments

Various piezoelectric polymers based on polyvinylidene fluoride (PVDF) are of interest for large aperture space-based telescopes. Dimensional adjustments of adaptive polymer films depend on charge deposition and require a detailed understanding of the piezoelectric material responses which are expected to deteriorate owing to strong vacuum UV, � -, X-ray, energetic particles and atomic oxygen exposure. We have investigated the degradation of PVDF and its copolymers under various stress environments detrimental to reliable operation in space. Initial radiation aging studies have shown complex material changes with lowered Curie temperatures, complex material changes with lowered melting points, morphological transformations and significant crosslinking, but little influence on piezoelectric d33 constants. Complex aging processes have also been observed in accelerated temperature environments inducing annealing phenomena and cyclic stresses. The results suggest that poling and chain orientation are negatively affected by radiation and temperature exposure. A framework for dealing with these complex material qualification issues and overall system survivability predictions in low earth orbit conditions has been established. It allows for improved material selection, feedback for manufacturing and processing, material optimization/stabilization strategies and provides guidance on any alternative materials.

A hybrid genetic algorithm for the optimal constrained web service selection problem in web service composition

Web service composition is an important problem in web service based systems. It is about how to build a new value-added web service using existing web services. A web service may have many implementations, all of which have the same functionality, but may have different QoS values. Thus, a significant research problem in web service composition is how to select a web service implementation for each of the web services such that the composite web service gives the best overall performance. This is so-called optimal web service selection problem. There may be mutual constraints between some web service implementations. Sometimes when an implementation is selected for one web service, a particular implementation for another web service must be selected. This is so called dependency constraint. Sometimes when an implementation for one web service is selected, a set of implementations for another web service must be excluded in the web service composition. This is so called conflict constraint. Thus, the optimal web service selection is a typical constrained ombinatorial optimization problem from the computational point of view. This paper proposes a new hybrid genetic algorithm for the optimal web service selection problem. The hybrid genetic algorithm has been implemented and evaluated. The evaluation results have shown that the hybrid genetic algorithm outperforms other two existing genetic algorithms when the number of web services and the number of constraints are large.

Using accelerometer, high sample rate GPS and magnetometer data to develop a cattle movement and behaviour model

The study described in this paper developed a model of animal movement, which explicitly recognised each individual as the central unit of measure. The model was developed by learning from a real dataset that measured and calculated, for individual cows in a herd, their linear and angular positions and directional and angular speeds. Two learning algorithms were implemented: a Hidden Markov model (HMM) and a long-term prediction algorithm. It is shown that a HMM can be used to describe the animal's movement and state transition behaviour within several “stay” areas where cows remained for long periods. Model parameters were estimated for hidden behaviour states such as relocating, foraging and bedding. For cows’ movement between the “stay” areas a long-term prediction algorithm was implemented. By combining these two algorithms it was possible to develop a successful model, which achieved similar results to the animal behaviour data collected. This modelling methodology could easily be applied to interactions of other animal species.

Validation of the Drinking Refusal Self-Efficacy Questionnaire - Revised in an Adolescent Sample (DRSEQ-RA)

Adolescent drinking is a significant issue yet valid psychometric tools designed for this group are scarce. The Drinking Refusal Self-Efficacy Questionnaire—Revised Adolescent Version (DRSEQ-RA) is designed to assess an individual's belief in their ability to resist drinking alcohol. The original DRSEQ-R consists of three factors reflecting social pressure refusal self-efficacy, opportunistic refusal self-efficacy and emotional relief refusal self-efficacy. A large sample of 2020 adolescents aged between 12 and 19 years completed the DRSEQ and measures of alcohol consumption in small groups. Using confirmatory factor analysis, the three factor structure was confirmed. All three factors were negatively correlated with both frequency and volume of alcohol consumption. Drinkers reported lower drinking refusal self-efficacy than non-drinkers. Taken together, these results suggest that the adolescent version of the Drinking Refusal Self-Efficacy Questionnaire (DRSEQ-RA) is a reliable and valid measure of drinking refusal self-efficacy.

A confirmatory factor analysis of the Toronto Alexithymia Scale (TAS-20) in an alcohol-dependent sample

Confirmatory factor analyses were conducted to evaluate the factorial validity of the Toronto Alexithymia Scale in an alcohol-dependent sample. Several factor models were examined, but all models were rejected given their poor fit. A revision of the TAS-20 in alcohol-dependent populations may be needed.